Kalman Filter Based Recursive Estimation of Slowly Fading Sparse Channel in Impulsive Noise Environment for OFDM Systems

摘要

In this paper, we propose a recursive sparse channel estimation algorithm in the presence of impulse noise. Firstly the channel impulse response and impulsive noise are jointly viewed as an unknown sparse vector. Then a novel recursive Kalman filtering based compressed sensing algorithm for joint channel and impulsive noise estimation is proposed by using the first order autoregressive model for tracking slowly time varying wireless channel. This algorithm can be extended also to quasi-static, block-fading scenario conveniently. Simulation results illustrate the efficiency of the proposed techniques in terms of the mean square error and bit error rate performance.